Systems and methods for northfinding

ABSTRACT

An apparatus for target location is disclosed. The apparatus includes a housing, which includes a range sensor to generate range data, an image sensor to generate image data, an inertial sensor to generate inertia data, and a processor. The processor is configured to receive the image data from the image sensor and determine a first orientation of the housing and receive the inertia data from the inertial sensor and modify the first orientation based on the inertia data to produce a modified orientation of the housing.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/817,688 filed Aug. 4, 2015 titled “Systems and Methods forNorthfinding” which claims the benefit of U.S. provisional patentapplication Ser. No. 62/032,724 filed Aug. 4, 2014 and entitled “Systemsand Methods for Northfinding,” which is incorporated herein by referencein its entirety.

BACKGROUND

The need for increased accuracy of target location determination is animportant performance requirement for handheld targeting systems.Previously, the digital magnetic compass (DMC) was the primary componentwithin systems used to determine the bearing (i.e., an angularmeasurement in the horizontal direction) between the observer and thetarget. The determined bearing was combined with a range to target, andinclination (i.e., an angular measurement in the vertical direction) ofthe target, and a location of the observer to provide athree-dimensional (3D) location of the target on the earth. However, anyerrors in the determined 3D location of the target may result incollateral damage (e.g., in a military context) when the target islocated near one or more non-threat targets, for example in cases ofurban engagement.

The horizontal bearing with respect to north of the target (“targetazimuth”) is typically the largest contributor to an error in thedetermined 3D location of the target. DMCs are susceptible to largeerrors caused by variations in a local magnetic field, which may becaused by steel structures such as buildings or vehicles, nearby powerlines, weapons, and even a tripod upon which a target locationdetermination system is mounted. Azimuth errors of only 6 degrees resultin target location errors of over 200 meters when the observer-to-targetrange is 2 kilometers.

BRIEF DESCRIPTION OF THE DRAWINGS

For a detailed description of exemplary embodiments of the disclosure,reference will now be made to the accompanying drawings in which:

FIG. 1 shows a perspective diagram of a system for determining alocation of a target;

FIG. 2 shows a block diagram of a system for determining a location of atarget in accordance with various examples;

FIG. 3 shows an example of use of a system for determining a location ofa target in accordance with various examples

FIG. 4 shows a flow chart of a method for determining a location of atarget in accordance with various examples; and

FIG. 5 shows a flow chart of a method for improved determination of thelocation of the center of the sun within an image in accordance withvarious examples.

NOTATION AND NOMENCLATURE

Certain terms are used throughout the following description and claimsto refer to particular system components. As one skilled in the art willappreciate, companies may refer to a component by different names. Thisdocument does not intend to distinguish between components that differin name but not function. In the following discussion and in the claims,the terms “including” and “comprising” are used in an open-endedfashion, and thus should be interpreted to mean “including, but notlimited to . . . .” Also, the term “couple” or “couples” is intended tomean either an indirect or direct electrical connection. Thus, if afirst device couples to a second device, that connection may be througha direct electrical connection, or through an indirect electricalconnection via other devices and connections.

DETAILED DESCRIPTION

The following discussion is directed to various embodiments of thedisclosure. Although one or more of these embodiments may be preferred,the embodiments disclosed should not be interpreted, or otherwise used,as limiting the scope of the disclosure, including the claims. Inaddition, one skilled in the art will understand that the followingdescription has broad application, and the discussion of any embodimentis meant only to be exemplary of that embodiment, and not intended tointimate that the scope of the disclosure, including the claims, islimited to that embodiment.

Alternatives to the above-described azimuth determination, hereinafterreferred to as “northfinding,” include celestial northfinding andinertial northfinding. Celestial northfinding relies on image processingof an image of the sun or stars, combined with knowledge of the time ofday and physical location of the targeting system, to determine thenorth direction and then applies this to determine a bearing to thetarget (toward which the targeting system is oriented). Inertialnorthfinding relies on high-precision gyroscopes or other inertialsensors to detect the rotation of the earth relative to the targetingsystem to determine the north direction and then applies this todetermine a bearing to the target (toward which the targeting system isoriented). Although inertial northfinding systems are more accurate thanthose using a DMC, such inertial northfinding systems are very expensiveand generally too large and unwieldy to be easily used in the field.

Current celestial northfinding solutions utilize a separate imagingsubsystem, which is integrated into an overall targeting system. FIG. 1shows a prior art targeting system 100, which includes components forcelestial northfinding. Targeting system 100 is embodied by a housing101 that includes a rangefinder 102, which may be directed at the target120 by orienting the line of sight 103 at the target 120. Operations ofthe targeting system 100 are generally carried out by a system processor105. The housing 101 also includes a daytime image sensor 106 to capturean image of the sun when the system 100 is used during the day and anighttime image sensor 108 to capture an image of the stars when thesystem 100 is used during the night. The daytime image sensor 106 maycomprise a charge coupled device (CCD) and utilize wide angle or fisheyeoptics to that allows the image sensor 106 to observe a hemisphericalview of the sky and ensure the sun is captured when the housing 101 isin a variety of orientations. The nighttime image sensor 108 may alsocomprise a CCD and utilize optics that provides a narrower (e.g.,between a 25-degree and 35-degree) field of view of the night sky.

Inside the housing 101, an image capture processor 110 receives datafrom the aforementioned sensors 106, 108, in addition to data from a GPSsubsystem (not shown), and/or other various subsystems. The daytimeimage sensor 106, nighttime image sensor 108, and the image captureprocessor 110 may be grouped together as a celestial northfinding module111. The processor 110 may access a database including sun angleinformation and star map information for given times of day andlocations on earth. As the user of the system 100 observes the target120, the image sensors 106, 108 observe the sun or stars. Based on timeof day and location of the system 100 (e.g., including its inclination,which may be subject to an inclinometer error), the informationcontained in the database is compared to the data provided by thesensors 106, 108 and the processor 110 determines an orientation of thesystem 100, which must then be corrected to determine a bearing of thetarget 120. The bearing is then provided to the system processor 105.Then, based on GPS data that indicates the position of the housing 101,the range to the target 120 given by rangefinder 102, and an inclinationof the target 120, the system processor 105 determines a 3D location ofthe target 120. The inclination of the target 120 may be provided, forexample, by an inclinometer. In some embodiments, the inclinometer isintegrated to an existing DMC (not shown) inside the housing 101, whichallows the DMC to generate data indicative of inclination of the housing101. The resulting azimuth determination and 3D location of the target120 is more accurate than when using a DMC alone.

However, the resulting targeting system 100 is expensive due tonecessitating the inclusion of the celestial northfinding module 111 inaddition to the system processor 105 and the optics already provided bythe rangefinder 102 and digital display 104. The calibration andspecialized optics required by the sensors 106, 108 can be prohibitive.For example, the optics of the celestial northfinding components ofsystem 100 must be individually calibrated to remove effects ofdistortion in lenses of the image capture subsystem 106, 108 in order toachieve a required accuracy.

Production logistics and qualification of the overall system 100 alsopresent problems. That is, such a targeting system 100 including thecelestial northfinding module 111 is currently not produced in a waythat allows the high production volume required of military systems. Forexample, current manufacturing methods require the housing 101 to besent to a supplier of the celestial northfinding module 111 forintegration and alignment. Additionally, suppliers have not qualifiedindividual subsystems to the MIL-STD-810 qualification; rather,qualification is only provided at the system level.

Finally, the targeting system 100 including celestial northfindingcomponents has practical disadvantages as well. During day-nightcrossover, illumination levels before sunrise and after sunset occludestars from the nighttime image sensor 108, and thus no reference pointis available to determine bearing to target 120. Similarly, insituations where top cover exists (e.g., clouds, foliage, or buildingobstacles), the upward facing sensors 106 and 108 cannot capture animage, and thus no reference point is available to determine bearing totarget 120.

To solve these and other problems, FIG. 2 shows a block diagram of asystem 200 for target location in accordance with various examples ofthe present disclosure. The target location system 200 includes ahousing 201, which contains a range sensor 202, an image sensor 206 forviewing targets and other objects, an inertial sensor 208, and a systemprocessor 210. The target location system 200 also includes an input 204for GPS or location data (which may also include data indicative of thetime of day) that is coupled to and provided to the processor 210. Insome embodiments, the location and/or time of day data may be generatedby a GPS sensor internal to the housing 201 (in which case the input 204comprises the GPS sensor), a GPS sensor external and coupled to theinput 204 of the housing 201, or through manual entry of a locationand/or time of day and date by way of an input device 204 such as akeypad, touchscreen, or the like. Unlike the system 100 shown in FIG. 1,target location system 200 does not require a separate celestialnorthfinding module 111 to capture images of celestial bodies. Althoughnot depicted, the housing 201 may also include elements similar to thosefound in FIG. 1, such as a digital display, which is part of the opticalsystem used to locate or view the target.

The range sensor 202 generates range data based on the distance to atarget at which the housing 201 is directed. In some embodiments, therange sensor 202 is a laser rangefinder, a sonic transceiver, or othertype of device to determine a distance to a target along a point of aim.The location data identifies a location of the housing 201. Inembodiments where the location data is generated by a GPS sensor (eitherinternal or external to housing 201), the GPS sensor may be one of manyknown types of such devices, and typically generates data that indicatesat least a latitude value, a longitude value, and an elevation value ofthe housing 201 location (the 3D location of the housing 201). Further,an inclinometer may be integrated to a DMC (not shown) in the housing201 to generate data related to the inclination of the target asexplained above, which may be used to determine the height of the targetrelative to the housing 201. Additionally, in certain situations whereGPS signals are not available, such as inside buildings, the locationdata of the housing 200 may be manually provided to the system processor210 through an input device 204, which may be integrated to or coupledto the housing 200.

As explained above, in accordance with various examples, the imagesensor 206 is integrated into an optical system used to view a target.The image sensor 206 may be, for example, a CMOS sensor, a CCD sensor,or other type of sensor to produce data indicative of a captured image.The optical system may consist of one or more lenses, a digital display,and also the range sensor 202. In this way, the optical system may beused to determine a distance to the target and also used to allow theimage sensor 206 to capture an image, thereby generating image data. Theinertial sensor 208 may include inertia-sensing devices such as anaccelerometer, a gyroscope or, more particularly, a MEMS gyroscope,which may be attached to or otherwise contained in the housing 201. Theinertial sensor 208 may comprise multiple individual sensors, forexample arranged orthogonally to one another, or a single multi-axissensor. The inertial sensor 208 generates inertia data, which mayindicate an angular displacement or acceleration of the housing 201.

The processor 210 receives data from each of the sensors or inputdevices 202, 204, 206, 208 and manipulates and/or processes this data todetermine a 3D location of a desired target. In particular, theprocessor 210 receives image data from the image sensor 206, such asdata generated when an image is captured of the sky. The image data maybe data that is indicative of a celestial body, such as the sun, themoon, a star other than the sun, a grouping of stars other than the sun,or one or more planets. Based at least in part on the image data, theprocessor 210 determines a first orientation of the housing 201 (i.e.,the orientation of the housing when the image was captured). Theprocessor 210 may also utilize information about the location of thehousing 201 (e.g., location and/or time of day data received from a GPSsensor) to determine the first orientation. For example, the processor210 may access a database including sun and/or star position informationfor given times of day and locations on earth. When the user of thesystem 200 captures an image of a celestial body, the informationcontained in the database is compared to the time of day and location ofthe system 200 and the image data and the processor 210 determines thefirst orientation of the housing 201 based on these comparisons. FIG. 4,discussed further below, provide additional detail about example systems and methods of determining an orientation of the housing 201 bycomparing a captured image with a database of known sun and/or starposition information.

When the housing 201 is moved from the first orientation such that thehousing 201 is now directed toward a target, the processor 210 receivesinertia data from the inertia sensor 208 that indicates a change inangular position. Based on the received inertia data, the processor 210modifies the first orientation to produce a modified orientation of thehousing 201. For example, if processor 210 determined that the firstorientation of the housing 201 was due north and the inertia dataindicated that the housing 201 had rotated 90 degrees to the right, theprocessor 210 would produce a modified orientation of due east. In caseswhere the housing 201 is directed at the target in the modifiedorientation, the modified orientation also indicates the bearing of thetarget relative to the housing 201.

Once a bearing to the target is determined by the processor 210, rangedata from the range sensor 202 and location data 204 from a GPS sensoror other input device are received by the processor 210. As above, basedon a known location of the housing 201, a bearing to the target, adistance to the target, and an inclination of the target, the processor210 determines a 3D location of the target. In certain embodiments wherea GPS device is included in or coupled to the housing 201, the GPSdevice may carry out portions of the above-described functionalityascribed to the processor 210. In any of the above scenarios, anon-transitory computer-readable medium may contain a set ofinstructions, which are executable by the processor 210, to cause theprocessor 210 to perform the functionality described herein. Such acomputer-readable medium is within the scope of the present disclosure.

Thus, in accordance with various examples, rather than have a separatecamera to observe the sun in order to find the target bearing, the userof the system 200 may simply point the system at the sun and cause theimage sensor 206 to capture an image. Similarly, at night, the usersimply points the system 200 at the stars and causes the image sensor206 to capture an image. Because there are no separate cameras required,the cost and complexity of the system 200 are reduced. Once thedirection of the sun or stars is determined by the system 200, the userreturns the line of sight to the target. During this line of sighttransition from the celestial object(s) to the target, the inertialsensor 208, which may be already integrated in the system 200, is usedto track the motion and, in essence, “transfer” the bearing to thetarget. As an example, certain DMC systems may have additional gyroscopecapabilities, which are leveraged as the inertial sensor 208 to produceinertial data.

As a result, if the user is under cover but can find any line of sightto the sky, the processor 210 of the system 200 is able to accuratelydetermine the first orientation and subsequently “transfer” thisorientation to determine a bearing to the target. Additionally, duringday-night crossover, the sun may be used as a basis for determining thefirst orientation even as it dips below the horizon, whereas in thesystem shown in FIG. 1, it is difficult or impossible to design anupward facing camera with sufficient field of view to accurately detectthe sun in such a position. Further, even in situations where the skymay not be viewable (e.g., in the case of intense cloud cover), if abody such as a landmark having a known location is viewable, image dataof the body having a known location may be similarly used by theprocessor 210 to determine a first orientation of the housing 201.

FIG. 3 shows an example 300 of the use of target location system 200.FIG. 3 illustrates a situation in which a user of the target locationsystem 200 is under cover 302, and thus the ability to view the sky bythe conventional upward-looking celestial northfinding module 111 isimpeded. However, in accordance with various examples, if the user isable to direct the target location system's image sensor 206 toward thesky (e.g., through a window, around a tree, or away from partial cloudcover) as shown by arrow 304, the processor 210 of the target locationsystem 200 is still able to determine a first orientation of the system200. Then, the user of the target location system 200 adjusts the system200, as shown by arrow 306, such that its line of sight is directed at atarget 320, as shown by arrow 308. During the motion 306, the processor210 utilizes data from the inertial sensor 208 to track the amount anddegree of motion to modify the determined first orientation to produce amodified orientation of the system 200. Based on the modifiedorientation, the distance to the target provided by the range sensor202, the location of the system 200 provided by the GPS sensor or otherinput device, and the inclination of the target, the processor 210 isable to determine a 3D location of the target.

Turning now to FIG. 4, a method 400 for target location using a portablehousing, such as housing 201, is shown in accordance with variousexamples of the present disclosure. The method 400 begins in block 402with receiving image data from an image sensor in the housing anddetermining a first orientation of the housing. As explained above, theimage sensor 206 may be integrated into an optical system used to view atarget and captures an image of the sky. This image data may beindicative of a celestial body, such as the sun, the moon, a star otherthan the sun, or a grouping of stars other than the sun. As will beexplained in further detail below, the first orientation of the housingmay be determined based on the location of the celestial body in thecaptured image and calculation or comparison that utilizes knownlocations of celestial bodies as a function of time.

For example, settings of the image sensor and other associated imagecapture devices (e.g., optics) are adjusted to provide suitable imagecapture in the particular environment. The user also may be prompted todirect the housing or device toward the sun. The user may provide aninput, such as pressing or activating a button, to indicate that thehousing is directed at the sun, or at least the sun is within the sceneto be captured by the image sensor. The image is acquired and the imagedata is provided by the image sensor to a processor in the housing. Theprocessor may apply an image processing technique to determine thecenter of the sun in the scene, which will be explained in furtherdetail below.

As another example where the housing is used at nighttime when the sunis not present, the center of an image of celestial bodies such as starsis determined from the captured scene. In these cases, a stellarpattern-matching technique may be applied to determine the orientationof the housing (e.g., including its elevation and azimuth) based on thecaptured celestial bodies. In these examples, the determination mayfirst include extracting the stars from the scene and creating a tableof star positions in the system field of view. This table of starpositions in the system field of view is compared to tables of knownstar patterns. This determines which particular patch of stars is beingobserved.

In both day and night scenarios, the position of celestial bodies(relative to the earth) is determined through a series of knownequations. The direction that the housing is pointed in terms of earthdirection (i.e., bearing and inclination) is determined by combiningthis information with the time and known location of the device. As willbe explained in further detail below, additional processing may beapplied in accordance with certain embodiments of the present disclosureto better extract the object of interest (e.g., sun or stars) fromclutter introduced by a real world environment.

The method 400 continues in block 404 with receiving inertia data froman inertial sensor and modifying the first orientation based on theinertia to produce a modified orientation of the housing. In someembodiments, the inertial sensor may be a gyroscope such as a MEMSgyroscope that generates data indicative of an angular displacement oracceleration of the housing from the first orientation to a secondorientation. For example, the user may direct the line of sight ordirection of the housing back to a target. In some cases, a prompt maybe provided to the user to indicate the appropriate time to change thedirection of the housing back to the target. Thus, the angulardisplacement or rotation may be “applied to” (i.e., used to alter) thefirst orientation to produce the modified orientation of the housing.For example, if the first orientation of the housing was due north andthe inertia data indicated that the housing had rotated 90 degrees tothe right, the modified orientation would be due east. In cases wherethe housing is directed at the target in the modified orientation, themodified orientation also indicates the bearing of the target relativeto the housing. As a result, the inertial data is, in effect, used to“transfer” the first orientation or bearing to a target that the housingis directed toward in the modified or second orientation. In someexamples, the modified orientation data may also incorporate aninclination of the target, for example based on an integratedinclinometer or a change in inclination—indicated by the inertialdata—relative to the first orientation. In some cases, the determinationof the centroid of the sun, the determination of the first orientation,and the determination of displacement based on inertial data may beperformed approximately in parallel, although this need not be the case.

The method 400 continues in block 406 with receiving range data from arange sensor in the housing and housing location data. The range datamay be provided by a laser rangefinder or other such device to determinerange to a target. As explained above, the housing location data may befrom a GPS sensor internal to the housing, external and coupled to thehousing, manually entered by a user input device, or other similar waysto acquire data indicative of the location of the housing. Based on themodified orientation data, the range data, and the housing locationdata, the method 400 then continues in block 408 with determining thetarget's location. As above, based on a known location of the housing201, a bearing to the target, a distance to the target, and aninclination of the target, the processor 210 determines a 3D location ofthe target.

As a result, if a user is under cover but can find any line of sight tothe sky, the method 400 is able to accurately determine the firstorientation toward a celestial body and subsequently “transfer” thisorientation to determine a bearing to the target. Additionally, duringday-night crossover, the sun may be used as a basis for determining thefirst orientation even as it dips below the horizon, whereas in thesystem shown in FIG. 1, it is difficult or impossible to design anupward facing camera with sufficient field of view to accurately detectthe sun in such a position. Further, even in situations where the skymay not be viewable (e.g., in the case of intense cloud cover), if abody such as a landmark having a known location is viewable, image dataof the body having a known location may be similarly used to determinethe first orientation of the housing.

Further, in certain examples of the present disclosure, although notexplicitly shown in the method 400, the method 400 may include firstdirecting the housing at the desired target, then to a celestial orother body having a known location, and then back to the desired target.As above, inertial data is generated when moving the housing todifferent orientations. However, due to the increased number of datapoints or measurements taken, a potential to reduce error in theinertial calculations is provided. For example, if during one of themotions a maximum rate for the gyroscope is exceeded, the two readingsmay be significantly different and a user is prompted to correct theerror (e.g., by re-performing the motion). In another example, theinertial data may be averaged to reduce errors introduced by noise inthe system.

As referenced above, certain environments may render ineffectiveconventional centroiding techniques to determine the location of acelestial body in a captured scene. For example, partial overhead coversuch as leaves, tree branches, and the like may obscure the sun makingits location more difficult. In other cases, strong reflections such asoff of buildings may cause a false positive identification of the sun.

Thus, determining the centroid of the sun may be subject to errorintroduced by a user or an environment, or false positiveidentifications. For example, conventional systems may utilize ablob-centroiding technique. However, clutter present in the capturedscene can obfuscate the exact location of the sun, present falsepositive identifications of the sun, or otherwise introduce uncertaintyin the computation where blobs of brightness (e.g., areas in a binary orblack and white image that contain a number of pixels above a threshold)may or may not be attributable to the actual location of the sun in thecaptured image. One example is where a building that reflects the sun isalso contained in the captured image along with the sun. As will beexplained below, in accordance with various examples of the presentdisclosure, an alternate centroiding technique is provided thatmitigates these and other issues.

In order to address these and other issues with conventional centroidingtechniques, and in accordance with various examples, FIG. 5 shows amethod 500 that leverages Hough circle transformations to generate amore accurate centroid for the sun while better rejecting clutter in thescene at the same time. The method 500 results in a reduction ininaccurate centroid positions where there are other bright regions inthe captured scene (e.g., glint, very bright clouds, reflectivebuildings). Further, the method 500 provides improved centroid detectioneven when the sun is partially obscured by objects in the scene, such asoverhanging branches, structures, and the like. That is, the method 500results in reduced error and/or incidences of false positiveidentification of the sun.

The method 500 begins in block 502 with capturing an image, whichincludes the sun, and generating a binned image by setting a thresholdso that pixels corresponding to a solar disc are set high while allothers are set low (e.g., creating a binary or white (high) and black(low) image by forcing all bright pixels above a certain value to whiteand forcing the remaining pixels to black). This binning separates theportions of the scene that include the solar disc from those thatcontain only clutter, eliminating much of the clutter from furtherconsideration or processing. The method 500 continues in block 504 withperforming a Hough circle transformation on the binned image generatedin block 502, with a radius search value set to be equivalent in pixelsto the expected radial size of the solar disc. The result of the Houghcircle transformation is a list of pixel positions and related metricvalues (or peaks) that correspond to the center of circles or arcshaving radii equal to or approximately equal to the search radius. Thevalue of each peak is determined by how close the radii of thecorresponding identified circle, semi-circle, or arc in the binned imageis to the search radius.

In block 506, the method 500 includes eliminating outliers in thedistribution of possible center positions and continues in block 508with determining the final position to be reported as the sun centroid.For example, the resulting list may be sorted by values of thecorrelation or peaks from greatest to smallest. The length of the listmay be limited by removing peak values and corresponding pixel positionsbelow a predetermined threshold value. Alternately, only a predeterminednumber of greatest peak values and corresponding pixel positions areretained. As a result, the center positions for the most likely centerpositions of the solar disc image are identified while further reducingerror and false positive identifications. Thus, the method 500 firstutilizes threshold binning to reduce the number of objects or clutter inthe scene, which may be misinterpreted by the Hough circle transform asarcs of a circle. In particular, the Hough circle transform reports verystrong peaks for circles or arcs of a certain radius, and by firsteliminating darker portions of the scene, much of the extraneous clutterwill not be considered by the Hough circle transform.

As explained above, the radius for the Hough circle transformcorresponds to the expected size or range of sizes of the solar disc.This further filters out other features or clutter in the scene, whichnormally confuse existing sun finding algorithms. Finally, filtering thepeaks reported by the Hough circle transform further eliminates falsereturns. In certain cases, an assumption is made that the solar discradius is already known. However, if the initial Hough transform doesnot yield a sufficient number of matches, then a feedback loop may beimplemented to iteratively refine the search radius if, for example, thesolar disc radius will change due to clouds, haze, camera exposure, andother factors.

The above discussion is meant to be illustrative of the principles andvarious embodiments of the present disclosure. Numerous variations andmodifications will become apparent to those skilled in the art once theabove disclosure is fully appreciated. For example, although the housingfor target location is generally described as including a digitaldisplay for viewing a target or other body, the digital display could bereplaced by direct view optics such as an optical sight glass, or otherviewing alternatives for sighting a target along a line of sight of thehousing. It is intended that the following claims be interpreted toembrace all such variations and modifications.

1. An apparatus for target location, comprising: a portable housingcomprising: a range sensor to generate range data; an image sensor togenerate image data; an inertial sensor to generate inertia data; and aprocessor to: receive the image data from the image sensor and determinea first orientation of the housing based on the image data; and receivethe inertia data from the inertial sensor and modify the firstorientation based on the inertia data to produce a modified orientationof the housing.
 2. The apparatus of claim 1 wherein the processorreceives the housing location data from one selected from the groupconsisting of: a global positioning system (GPS) sensor external to thehousing, a GPS sensor internal to the housing, and a user input device.3. The apparatus of claim 1 wherein the range sensor comprises a laserrangefinder.
 4. The apparatus of claim 1 wherein the inertial sensorcomprises a MEMS gyroscope.
 5. The apparatus of claim 1 wherein theimage data comprises data indicative of at least one celestial body andwhen the processor determines the first orientation, the processorcompares the image data to known parameters for the at least onecelestial body at a given time of day and the location indicated by thehousing location data to determine the first orientation.
 6. Theapparatus of claim 5 wherein the celestial body comprises at least oneselected from the group consisting of: the sun, the moon, one star otherthan the sun, a grouping of stars other than the sun, and one or moreplanets.
 7. The apparatus of claim 1 wherein the image data comprisesdata indicative of a body having a known location and when the processordetermines the first orientation, the processor compares the locationindicated by the housing location data and the known location of thebody.
 8. The apparatus of claim 1 wherein the processor is furtherconfigured to: receive the range data from the range sensor and housinglocation data; and determine the target location based on the modifiedorientation data, the range data, and the housing location data.
 9. Amethod for target location using a portable housing, comprising:receiving image data from an image sensor in the housing and determininga first orientation of the housing based on the image data; andreceiving inertia data from an inertial sensor in the housing andmodifying the first orientation based on the inertia data to produce amodified orientation of the housing.
 10. The method of claim 9 furthercomprising: receiving range data from a range sensor in the housing andhousing location data; and determining the target location based on themodified orientation data, the range data, and the housing locationdata.
 11. The method of claim 9 wherein the image data comprises dataindicative of at least one celestial body and the method furthercomprises: comparing the image data to known parameters for the at leastone celestial body at a given time of day and the location indicated bythe housing location data to determine the first orientation.
 12. Themethod of claim 11 wherein the celestial body comprises at least oneselected from the group consisting of: the sun, the moon, one star otherthan the sun, a grouping of stars other than the sun, and one or moreplanets.
 13. The method of claim 9 wherein the image data comprises dataindicative of a body having a known location and the method furthercomprises determining the first orientation by comparing the locationindicated by the housing location data and the known location of thebody.
 14. A non-transitory computer-readable medium comprisinginstructions that, when executed by a processor, cause the processor to:receive image data from an image sensor and determine a firstorientation of a portable housing for the processor based on the imagedata; and receive inertia data from an inertial sensor and modify thefirst orientation based on the inertia data to produce a modifiedorientation of the housing.
 15. The non-transitory computer-readablemedium of claim 14 wherein the instructions further cause the processorto: receive range data from a range sensor and housing location data;and determine a location of a target based on the modified orientationdata, the range data, and the housing location data.
 16. Thenon-transitory computer-readable medium of claim 14 wherein the imagedata comprises data indicative of at least one celestial body and theinstructions further cause the processor to: compare the image data toknown parameters for the at least one celestial body at a given time ofday and the location indicated by the housing location data to determinethe first orientation.
 17. The non-transitory computer-readable mediumof claim 16 wherein the celestial body comprises at least one selectedfrom the group consisting of: the sun, the moon, one star other than thesun, a grouping of stars other than the sun, and one or more planets.18. The non-transitory computer-readable medium of claim 14 wherein theimage data comprises data indicative of a body having a known locationand the instructions further cause the processor to determine the firstorientation by comparing the location indicated by the housing locationdata and the known location of the body.
 19. The apparatus of claim 2wherein the user input device is selected from the group consisting of:a keypad; and a touchscreen.
 20. The non-transitory computer-readablemedium of claim 17 wherein, when the celestial body is the sun, theinstructions causing the processor to receive image data from an imagesensor and determine a first orientation of the portable housing areoperable during day-night crossover.